Opinion: Will AI Rescue The Chemical Industry From Retirement Crisis?

The “silver tsunami” of baby boomer retirements is familiar enough in the abstract. A recent conversation I had with a chemical executive cast it in concrete.

“A quarter of my workforce will be retiring in the next 10 years,” he told me. “And it’s not a quarter of the back office. It’s a quarter in the manufacturing operation. And there’s no pipeline.”

This company is far from being an exception. Complicating the staffing crunch is an industry squeezed by commoditization, global overcapacity, geopolitical challenges, policy uncertainty and increasing regulatory scrutiny in traceability and sustainability, according to a 2025 Chemical Industry Outlook from Deloitte.

The instinctive response to the exit of the experience is fostering their replacement by new talent. That has to be a big part of the story in chemicals. Yet the hard demographic truth is, in the industry’s biggest markets, companies must retain — and, increasingly, retrain — early and midcareer staff to fill different or expanded roles, and AI automation and knowledge-sharing technologies will be crucial in enabling that.

‘Marketing’ to Gen Z is Important

First, though, a few words on messaging and marketing to prospective Gen Z employees, which is rightly a focus of chemical makers. My take is that the industry is already doing many of the right things. Look at the websites of major firms (BASF, Dow, Sinopec, LG chem, Sabic and Lyondell Basell, among others), and you’ll find terminology that appeals to the interests of the young — and should appeal to everyone’s interests: sustainability, environmental protection, science, innovation, advanced materials, circular economy, clean energy and climate protection among them.

There’s still work to be done to help prospective future employees understand that the key technologies of the future will depend on the chemical industry and its people. Wind turbines, solar panels, advanced batteries, water-treatment solutions, carbon capture and storage, hydrogen production and storage — all ultimately depend on the chemical business. Don’t forget, either, that generative AI works its magic thanks to the chemical industry’s many contributions to the GPUs (graphical processing units) of so many server farms.

AI is Part of the Gen Z Hiring Story

The emergence of generative and agentic AI could positively impact the chemical industry’s hiring of young talent in a couple of ways. Its ability to write code is shrinking the pool of entry-level jobs for technical people across industries and, in particular, pushing students away from computer science. The chemical industry should exploit that. Given AI’s ability to generate novel compounds and materials and reimagine complex processes that could ultimately benefit the planet, this business has a good story to tell young AI specialists. 

The industry should continue to lean into traditional ways of boosting the talent pipeline, such as internships, and collaborate with educational institutions, including trade schools, to align curricula with changing industry needs. Once on board, mentorship programs help young employees establish their footing and plan for their futures. On-the-job training across different functions in the organization may be as old as work itself, but AI-augmented, highly targeted microlessons and relevant, in-depth curricula will help fill skills gaps more quickly than possible before.

But again, the reality of birth rates falling below replacement levels across the developed world means chemical companies must do more with lower headcounts. AI’s fast-improving abilities will help workers do more with less across the board, but early returns indicate that knowledge work will experience the biggest disruptions. That opens doors to the transition of early and mid-career back-office staff to more front-line positions in operations.

AI Will (Finally) Fulfill the Promise of Knowledge Management

The learning curve to entering the chemical industry is steep. But that AI-powered training also applies to reskilling the workers you already have. Add to that conversational AI that is capable of answering questions specific to job-related tasks, and you can enable internal career pivots like never before.

The AI models delivering those answers will feed off all sorts of documentation (from user manuals to process diagrams to notes from completed maintenance work orders), but also the deliberately recorded expertise of experienced production personnel. That preserves otherwise perishable institutional memory and expands the roles of those whose jobs were merely to execute into those of de facto trainers and knowledge pollinators. In the process, tribal knowledge becomes universal knowledge.

An exciting benefit is that ambitious employees will have new ways to gain insight and expertise in various areas of the business. Procurement professionals can get deeper expertise in logistics; logistics folks can understand the intricacies of planning; manufacturing staff can get to know R&D and product development better. That sort of shared understanding makes the whole business run more smoothly.

Talent Management Gets Trickier

Cloud-based architectures enabling both AI and the sharing of cross-functional data are basic requirements here. As roles morph, expand and evolve much more quickly than in the past, talent management systems capable of tracking skills and interests, suggesting future roles, and assigning and monitoring training become more important. And you can’t expect employees to embrace new systems — even ones that are clearly in their and the company’s best interests — without solid internal communications and change management.

There’s no single answer to the question of how the chemical companies will meet growing demand with fewer FTEs. But there are several answers, and the chemical industry should be pursing them all.